Calculation method of correlation search window ignoring some pixel data and navigation device using the same

ABSTRACT

There is provided a navigation device including an image sensor and a processor. The image sensor outputs a reference frame and a comparison frame. The processor calculates a correlation search window by changing a relative position of the comparison frame with respect to the reference frame. The processor ignores a part of pixel data of the comparison frame without being processed while calculating each correlation value of the correlation search window to reduce total computation load.

CROSS REFERENCE TO RELATED APPLICATION

The present application is a continuation application of U.S. Ser. No.16/152,663, filed on Oct. 5, 2018, the disclosure of which is herebyincorporated by reference herein in its entirety.

BACKGROUND 1. Field of the Disclosure

This disclosure generally relates to a navigation device and, moreparticularly, to a navigation device that ignores a part of pixel dataof an image frame in calculating a correlation search window to reducethe calculating power consumption and a calculation method of thecorrelation search window, wherein said correlation search window is forcalculating displacement and subpixel motion.

2. Description of the Related Art

Although the touch panel has been broadly applied to human-machineinterfaces, in some scenarios a navigation device is still necessary inorder to conduct an interaction with an imaging display system.

In some types of navigation devices, an image sensor is adopted toacquire images, and the position tracking is performed by calculating afeature variation between images. However, a navigation device ispreferably has a low power consumption, and each device element needs toreduce its consumed power in operation especially for a wirelessnavigation device. Nowadays, a high sampling rate is adopted in thenavigation device to improve the accuracy such that a frequency ofcalculating the feature variation is increased at the same time toincrease the total power consumption.

Accordingly, it is necessary to provide a navigation device that canreduce the consumption power of the device during the position tracking.

SUMMARY

The present disclosure provides a navigation device and a calculationmethod of a correlation search window thereof that ignore a part ofpixel data of an image frame during calculating a correlation searchwindow to reduce the consuming power in calculation.

The present disclosure further provides a navigation device thatperforms the position tracking by using a correlation search windowcalculated by image frames of different resolution.

The present disclosure further provides a navigation device and acalculation method of a correlation search window thereof that perform asecond calculation on calculated correlation values of a correlationsearch window.

The present disclosure further provides a navigation device capable ofcalculating subpixel motion. When a calculated correlation peak islocated at predetermined positions of a correlation search window, thenavigation device projects some adjacent correlation values around thecorrelation peak from other adjacent correlation values by mirrorreflection, and calculates the subpixel motion according to thecorrelation peak and adjacent correlation values thereof.

The present disclosure provides a navigation device including an imagesensor and a processor. The image sensor is configured to output areference frame and a comparison frame, wherein the reference frame isan image frame prior to the comparison frame. The processor isconfigured to calculate a correlation search window by changing arelative position of the comparison frame with respect to the referenceframe, wherein the processor ignores a part of pixel data of thereference frame in calculating each correlation value of the correlationsearch window, calculate a correlation peak of the correlation searchwindow, calculate full-resolution correlation values of the correlationpeak and adjacent correlation values thereof, respectively, according tothe comparison frame and the reference frame without ignoring pixeldata, and mirror project the full-resolution correlation values of theadjacent correlation values within the correlation search window as apart of adjacent correlation values, which are outside the correlationsearch window, of the correlation peak when the correlation peak is atan edge position of the correlation search window.

The present disclosure further provides a navigation device including animage sensor and a processor. The image sensor is configured to output areference frame and a comparison frame, wherein the comparison frame isan image frame prior to the comparison frame. The processor isconfigured to calculate a correlation search window by changing arelative position of the comparison frame with respect to the referenceframe, not ignore any pixel data of the comparison frame whilecalculating inner correlation values of the correlation search window,and ignore a part of pixel data of the comparison frame whilecalculating edge correlation values surrounding the inner correlationvalues of the correlation search window.

The present disclosure further provides a calculation method of acorrelation search window of a navigation device. The navigation deviceincludes an image sensor and a processor. The calculation methodincludes the steps of: sequentially outputting, by the image sensor, areference frame and a comparison frame; calculating, by the processor, acorrelation search window by changing a relative position of thecomparison frame with respect to the reference frame; not ignoring anypixel data of the reference frame while calculating, by the processor,inner correlation values of the correlation search window; and ignoringa part of pixel data of the reference frame while calculating, by theprocessor, edge correlation values surrounding the inner correlationvalues of the correlation search window.

In the navigation device and the calculation method of a correlationsearch window of the present disclosure, said ignoring is referred tothat even though the image sensor is arranged to output pixel data ofall pixels, the processor does not calculate pixel data of the ignoredpixels during calculating correlation values using multiplication orsubtraction, wherein, according to different applications, the pixeldata of the ignored pixels is not stored in a memory or is still storedin the memory to be used in the following operation.

The navigation device of the present disclosure does not reduce thepower consumption by turning off a part of pixels of an image sensor incapturing an image frame. A read circuit (e.g., correlated doublesampling, CDS) still reads pixel data of all pixels of a pixel array,and the pixel data is sent to a processor. The processor ignores a partof pixel data of a comparison frame while calculating correlation valuesof a correlation search window.

BRIEF DESCRIPTION OF THE DRAWINGS

Other objects, advantages, and novel features of the present disclosurewill become more apparent from the following detailed description whentaken in conjunction with the accompanying drawings.

FIG. 1 is a schematic diagram of a navigation device according to oneembodiment of the present disclosure.

FIGS. 2A-2D are schematic diagrams of calculating a correlation searchwindow using a navigation device according to a first embodiment of thepresent disclosure.

FIGS. 3A-3B are schematic diagrams of calculating a correlation searchwindow using a navigation device according to a second embodiment of thepresent disclosure.

FIGS. 4A-4D are schematic diagrams of calculating a correlation searchwindow using a navigation device according to a third embodiment of thepresent disclosure.

FIGS. 5A-5G are schematic diagrams of calculating a correlation searchwindow using a navigation device according to a fourth embodiment of thepresent disclosure.

FIG. 6 is a schematic diagram of setting a displacement thresholdaccording to one embodiment of the present disclosure.

FIG. 7 is a flow chart of an operating method of a navigation deviceaccording to one embodiment of the present disclosure.

FIG. 8 is a comparison diagram of calculation results between the first,the third and the fourth embodiments of the present disclosure.

DETAILED DESCRIPTION OF THE EMBODIMENT

It should be noted that, wherever possible, the same reference numberswill be used throughout the drawings to refer to the same or like parts.

The navigation device of the present disclosure is adapted to variousdevices such as an optical mouse, an optical finger navigator (OFN), anoptical remote controller and an optical game tool that adopt an imagesensor to capture image frames and calculate a correlation search windowfor tracking positions. Although the following embodiments are describedby using an optical mouse as an example, a person skilled in the artwould understand the operation applied to other types of the navigationdevice after understanding the descriptions below. Furthermore, itshould be mentioned that in some applications of the navigation device,a light source is not necessary.

Referring to FIG. 1, it is a schematic diagram of a navigation device100 according to one embodiment of the present disclosure. Thenavigation device 100 includes a light source 11, an image sensor 13, aprocessor 15 and a memory 17. The navigation device 100 is used toperform a relative motion with respect to a work surface S, wherein saidrelative motion is implemented by the movement of at least one of thenavigation device 100 and the work surface S.

The light source 11 and the image sensor 13 are electrically coupled tothe processor 15 to be controlled thereby. The processor 15 accessesdata in the memory 17 while calculating displacement.

The light source 11 is, for example, a light emitting diode or a laserdiode, and emits light of an identifiable spectrum to illuminate thework surface S, e.g., emitting red light and/or infrared light.

The image sensor 13 includes, for example, a CCD image sensor, a MOSimage sensor or other light sensors, which has a plurality of pixelsarranged in an array to sequentially acquire image frames F at asampling rate corresponding to the lighting of the light source 11, andthe acquired image frames F are sent to the processor 15 forpost-processing. In the embodiment without the light source 11, theimage sensor 13 captures ambient light bounces off a target and outputsimage frames F at a predetermined frame rate.

The processor 15 is, for example, a digital signal processor (DSP), amicro controller unit (MCU) or an application specific integratedcircuit (ASIC) that calculates, using predetermined software and/orhardware codes, displacement with respect to the work surface Saccording to the image frames F successively outputted by the imagesensor 13. The calculated displacement may or may not include subpixelscale depending on the required calculation accuracy.

The memory 17 includes a non-volatile memory and/or a volatile memory,and used to permanently store the algorithm and parameters (e.g., thedisplacement threshold below, but not limited to) used in calculatingdisplacement, and temporarily store pixel data of image frames F (e.g.,reference frame and comparison frame) in operation of the navigationdevice 100.

FIGS. 2A-2D are schematic diagrams of calculating a correlation searchwindow using a navigation device 100 according to a first embodiment ofthe present disclosure. In this embodiment, the image sensor 13sequentially outputs a reference frame F1 and a comparison frame F2(e.g., separated by at least one sampling period), wherein thecomparison frame F2 is a current frame and the reference frame F1 is animage frame outputted prior to the comparison frame F2 and has beenstored in the memory 17. The processor 15 calculates a correlationsearch window CSW according to the reference frame F1 and the comparisonframe F2, and calculates the displacement with respect to the worksurface S according to the calculated CSW. In this embodiment, thecorrelation search window CSW is described by a 3×3 correlation valuearray (as shown in FIG. 2B) as an example.

For example, the processor 15 calculates the correlation search windowCSW by changing a relative position of the comparison frame F2 withrespect to the reference frame F1, e.g., FIG. 2B showing that CSWincludes 9 correlation values C1 to C9, wherein each correlation valueC1 to C9 of CSW is a sum of multiplication or a sum of subtractionbetween corresponding pixels of the comparison frame F2 and thereference frame F1 at an associated relative position. In FIGS. 2A, 2Cand 2D, F1-A to F1-D refer to four corner pixels of the reference frameF1, and F2-A to F2-D refer to four corner pixels of the comparison frameF2.

For example, for calculating the correlation value C5, the processor 15fully overlaps the comparison frame F2 with the reference frame F1, andthen respectively calculates a multiplication operation or a subtractionoperation of corresponding pixel data in a pixel-by-pixel manner (e.g.,a number of 13×13 operations), and then calculates a sum of 13×13multiplication values or a sum of 13×13 subtraction values. Theprocessor 15 takes the calculated sum of multiplication or sum ofsubtraction as the correlation value C5.

For example, for calculating the correlation value C2, the processor 15moves the comparison frame F2 upward by one pixel with respect to thereference frame F1, as shown in FIG. 2C. The processor 15 thenrespectively calculates a multiplication operation or a subtractionoperation of corresponding pixel data within an overlap area in apixel-by-pixel manner (e.g., a number of 12×13 operations), and thencalculates a sum of 12×13 multiplication values or a sum of 12×13subtraction values. The processor 15 takes the calculated sum ofmultiplication or sum of subtraction as the correlation value C2.Depending on different applications, the non-overlapped pixels (e.g.,those filled with lines slant in a single direction in FIG. 2C) are alsomultiplied or subtracted.

For example, for calculating the correlation value C9, the processor 15moves the comparison frame F2 rightward and downward by one pixel withrespect to the reference frame F1, as shown in FIG. 2D. The processor 15then respectively calculates a multiplication operation or a subtractionoperation of corresponding pixel data within an overlap area in apixel-by-pixel manner (e.g., a number of 12×12 operations), and thencalculates a sum of 12×12 multiplication values or a sum of 12×12subtraction values. The processor 15 takes the calculated sum ofmultiplication or sum of subtraction as the correlation value C9.Similarly, depending on different applications, the non-overlappedpixels are also multiplied or subtracted.

Other correlation values C1, C3 to C4 and C6 to C8 are calculatedsimilar to those of FIGS. 2C and 2D only relative positions between thecomparison frame F2 and the reference frame F1 are different, and thusdetails of the calculation are not repeated herein. The 3×3 correlationvalue array includes 9 correlation values corresponding to 9 relativepositions of the comparison frame F2 with respect to the reference frameF1. In a different application, the correlation search window isselected as a 5×5 correlation value array, and the processor 15 needs tocalculate 25 correlation values. The 5×5 correlation value arrayincludes 25 correlation values corresponding to 25 relative positions ofthe comparison frame F2 with respect to the reference frame F1.

Referring to FIGS. 3A-3B, they are schematic diagrams of calculating acorrelation search window using a navigation device according to asecond embodiment of the present disclosure. To reduce computation loadof calculating the correlation search window CSW, the processor 15ignores a part of pixel data of the comparison frame F2 whilecalculating each correlation value (e.g., C1 to C9 in FIG. 2B) of CSW.In one non-limiting embodiment, the ignored pixel data (e.g., filledpixels in FIG. 3A) and the rest pixel data (e.g., blank pixels in FIG.3A) in the comparison frame F2 are distributed as a chessboard pattern,but the present disclosure is not limited thereto as long as a part ofpixel data of the comparison frame F2 is not calculated in calculatingthe sum of amplification or the sum of subtraction.

For example referring to FIG. 3B, it is a schematic diagram ofcalculating a correlation value C2 in the second embodiment, i.e. thecomparison frame F2 moving 1-pixel upward with respect to the referenceframe F1. In FIG. 3B, within an overlap area (not filled by lines slantin a single direction) of the reference frame F and the comparison frameF2, the blank pixel (not filled by any slant line) are not calculated.Accordingly, compared to FIG. 2C in which 12×13 times of operations(multiplication or subtraction) are needed to calculate the correlationvalue C2 due to the full-resolution (no pixel data being ignored)comparison frame F2 being used, FIG. 3B only needs about a half ofcomputation for obtaining the correlation value C2 such that the powerconsumption in calculation is effectively reduced.

Similarly, in calculating other correlation values C1 and C3 to C9 inFIG. 2B by the second embodiment, the processor F2 ignores a part ofpixel data of the comparison frame F2 to effectively reduce the powerconsumption during calculation.

Referring to FIGS. 4A to 4D, they are schematic diagrams of calculatinga correlation search window using a navigation device according to athird embodiment of the present disclosure. In this embodiment, theprocessor 15 changes the relative position of the comparison frame F2with respect to the reference frame F1 inupward/downward/leftward/rightward directions (by one and two pixels) ina way similar to those shown in FIGS. 2C and 2D to obtain correlationvalues of D1 to D25 of a correlation search window CSW4; for example,moving the comparison frame F2 leftward and upward with respect to thereference frame F1 by 2 pixels to obtain the correlation value D1,moving the comparison frame F2 upward with respect to the referenceframe F1 by 2 pixels to obtain the correlation value D3, and so on. Theprocessor 15 then calculates a correlation peak (i.e. maximumcorrelation value) of the correlation search window CSW4, and calculatesdisplacement according to the correlation peak.

For example in an embodiment without using a peak prediction algorithm(for predicting a position of a correlation peak), when the correlationpeak is at a center of CSW4 (as shown in FIG. 4B), it means that thedisplacement is 0. When the correlation peak is at a lower-right cornerof CSW4 (as shown in FIG. 4C), it means that the displacement is 2pixels rightward and 2 pixels downward. When the correlation peak is ata position of CSW4 as shown in FIG. 4D, it means that the displacementis 2 pixels rightward and 1 pixel downward. In this case subpixel motionis not considered, and thus a position change of only the correlationpeak is considered.

When the subpixel motion is considered, the processor 15 calculates thesubpixel motion according to the correlation peak and adjacentcorrelation pixels thereof. For example referring to FIG. 4B again, itis assumed that the correlation peak (black position) is located at acenter position of CSW4, and there are 8 adjacent correlation pixels(filled with dots) surrounding the correlation peak. As in this stagethe correlation peak and the 8 adjacent correlation values arecalculated using the partial-resolution comparison frame F2 (i.e.ignoring partial pixel data as shown in FIGS. 3A to 3B), to increase theposition accuracy, the processor 15 further calculates (for the secondtime) full-resolution (referred to no ignored pixel data) correlationvalues of the correlation peak and the 8 adjacent correlation values,respectively, according to the comparison frame F2 without ignoringpixel data (as shown in FIGS. 2C and 2D) and the reference frame F1. Theprocessor 15 calculates the subpixel motion according to thefull-resolution correlation peak and the full-resolution adjacentcorrelation values.

However, while calculating the full-resolution correlation values forthe second time, the processor 15 does not need to readback the full13×13 comparison frame F2 again. As an example, referring to a centerposition D13 in CSW4 of FIG. 4A, the first partial-resolutioncalculation result already contains a sum of products of 84 pixels of F2(out of the 13×13 total pixels or 169 pixels of F2). Let's call thefirst partial-resolution calculation result as P1. For the secondfull-resolution calculation, the processor 15 only needs to retrieve therest 85 pixels of F2 from the memory 17 that are skipped in the firstpartial-resolution calculation and calculates the remaining sum ofproducts on the 85 pixels. Let's call the result of the sum of productsof the rest 85 pixels as P2. So the full-resolution calculation resultfor D13=P1+P2. The full-resolution calculations for the 8 adjacentcorrelation values surrounding D13 is similar. The 85 pixels of F2 thatare retrieved from the memory 17 previously is shifted by the processor15 in all 8 directions to get their remaining sum of products which isthen added to their first partial-resolution calculation result.

The subpixel motion is calculated by, for example, using valueweightings of the correlation peak and the maximum adjacent correlationvalue (or including the second maximum adjacent correlation value) amongthe 8 adjacent correlation values. Therefore, if the subpixel motion isnot calculated, FIG. 4B indicates no displacement. However, if thesubpixel motion is considered, FIG. 4B indicates non-zero displacement,and the motion is toward a direction of the maximum adjacent correlationvalue from the correlation peak and smaller than one-pixel distance.

In addition, when the correlation peak is at an edge position of thecorrelation search window CSW4 such as a corner position shown in FIG.4C, the processor 15 also calculates full-resolution correlation valuesof the correlation peak and the adjacent correlation values within CSW4(e.g., three adjacent correlation values a, b and c herein) according tothe comparison frame F2 without ignoring pixel data and the referenceframe F1. As for the adjacent correlation values outside CSW4 (e.g., a′,b′ and c′ herein), the processor 15 does not calculate the sum ofmultiplication or subtraction of corresponding pixel data but mirrorprojects the full-resolution correlation values of the adjacentcorrelation values (e.g., a, b and c herein) within the correlationsearch window CSW4 as a part of adjacent correlation values (e.g., a′,b′ and c′ herein), which are outside the correlation search window CSW4,of the correlation peak. For example, a′=a, b′=b and c′=c. Finally, theprocessor 15 calculates the subpixel motion according to valueweightings of the correlation peak and adjacent correlation values(e.g., a, b, c and a′, b′, c′ herein). The calculation in FIG. 4D issimilar to FIG. 4C, i.e. the processor 15 calculating full-resolutioncorrelation values of the correlation peak (black position) and inneradjacent correlation values (dotted positions), and then mirrorprojecting outer adjacent correlation values from the inner adjacentcorrelation values, and thus details thereof are not repeated herein.

Referring to FIGS. 5A to 5G they are schematic diagrams of calculating acorrelation search window using a navigation device according to afourth embodiment of the present disclosure. In this embodiment, theprocessor 15 also changes the relative position of the comparison frameF2 with respect to the reference frame F1 to calculate a 5×5 correlationsearch window CSW5. Different from the above third embodiment, in thisembodiment the processor 15 does not ignore any pixel data of thecomparison frame F2 while calculating 9 inner correlation values (e.g.,F1 to F9) of the correlation search window CSW5, i.e., calculating theinner correlation values F1 to F9 by 9 relative positions using afull-resolution comparison frame F2 and a reference frame F1. However,the processor 15 ignores a part of pixel data of the comparison frame F2while calculating 16 edge correlation values (e.g., D1 to D16) of thecorrelation search window CSW5, i.e. calculating the edge correlationvalues D1 to D16 by 16 relative positions using a partial-resolutioncomparison frame F2 and the reference frame F1. Accordingly, thecomputation load is effectively reduced in calculating the edgecorrelation values.

Similarly, after the 5×5 correlation search window CSW5 is obtained, theprocessor 15 calculates a correlation peak of CSW5. If it is notnecessary to calculate subpixel motion, the displacement is calculateddirectly according to a position of the correlation peak. For example,in the case without using the peak prediction algorithm, FIG. 5Bindicates no displacement, FIG. 5C indicates 1 pixel rightward and 1pixel downward motion, FIG. 5D indicates 1 pixel rightward motion, FIG.5E indicates 2 pixels rightward and 2 pixels downward motion, FIG. 5Findicates 2 pixels rightward and 1 pixel downward motion, and FIG. 5Gindicates 2 pixels rightward motion.

If it is desired to calculate subpixel motion, the processor 15 alsocalculates the subpixel motion according to a correlation peak and 8adjacent correlation values thereof in CSW5.

For example, when the correlation peak is at a position of the edgecorrelation values (e.g., shown in FIGS. 5E and 5G) of the correlationsearch window CSW5, the processor 15 further calculates full-resolutioncorrelation values of the correlation peak (e.g., black position inFIGS. 5E-5G) and the adjacent correlation values (e.g., positions filledwith small dots in FIGS. 5E-5G) within CSW5, respectively, according tothe comparison frame F2 without ignoring pixel data (e.g., shown inFIGS. 2C and 2D) and the reference frame F1 because these correlationvalues were calculated using a partial-resolution comparison frame F2.

Next, the processor 15 further mirror projects the full-resolutioncorrelation values of the adjacent correlation values within thecorrelation search window CSW5 (e.g., a, b and c herein) as a part ofadjacent correlation values (e.g., a′, b′ and c′ herein), which areoutside the correlation search window CSW5, of the correlation peak. Forexample, a′=a, b′=b and c′=c. Finally, the processor 15 calculates thesubpixel motion according to value weightings of the correlation peakand adjacent correlation values thereof (e.g., a, b, c and a′, b′ and c′herein).

In addition, when the correlation peak is at a position of the innercorrelation values of the correlation search window CSW5 but not at acenter position (e.g., as shown in FIGS. 5C and 5D), the processor 15further calculates full-resolution correlation values of the adjacentcorrelation values at positions of the edge correlation values (e.g.,positions filled with small dots in FIGS. 5C-5D), respectively,according to the comparison frame F2 without ignoring pixel data (e.g.,as shown in FIGS. 2C and 2D) and the reference frame F1 because thesecorrelation values were calculated using a partial-resolution comparisonframe F2. Finally, the processor 15 calculates the subpixel motionaccording to value weightings of the correlation peak and adjacentcorrelation values thereof.

In some embodiments, the present disclosure further predicts thecorrelation peak in conjunction with a peak prediction algorithm. Thefinal displacement is equal to the predicted displacement plus thedisplacement (non-subpixel motion or subpixel motion) calculated byusing the correlation search window as mentioned above.

Referring to FIG. 7, it is a flow chart of an operating method of anavigation device according to one embodiment of the present disclosure,which is adaptable to a calculation method of a correlation searchwindow of a navigation device 100 of FIG. 1. The calculation methodincludes: storing a reference frame F1 in a memory 17 (Step S71);outputting a comparison frame F2 by an image sensor 13 (Step S73); andchanging, by a processor 15, a relative position of the comparison frameF2 with respect to the reference frame F1 to calculate a correlationsearch window, wherein the processor 15 ignores a part of pixel data ofthe comparison F2 while calculating at least a part of correlationvalues of the correlation search window (Step S75). As mentioned above,the comparison frame F2 is a current frame, and the reference frame F1is an image frame outputted prior to the comparison frame F2.

When the correlation search window is the 3×3 correlation value array(FIG. 2B) or the 5×5 correlation value array (FIG. 4A), the processor 15ignores a part of pixel data of the comparison frame F2 duringcalculating each correlation value of the correlation search window.

When the correlation search window is the 5×5 correlation value array(FIG. 5A), the processor 15 does not ignore any pixel data duringcalculating 9 inner correlation values (e.g., F1 to F9 shown in FIG. 5A)of the correlation value array. However, the processor 15 ignores a partof pixel data of the comparison frame F2 during calculating 16 edgecorrelation values (e.g., D1-D16 shown in FIG. 5A) of the correlationvalue array.

As mentioned above, the processor 15 is arranged to calculate or not tocalculate the subpixel displacement to accordingly determine whether tore-calculate the correlation values, which are firstly obtained using apartial-resolution comparison frame F2 (e.g., FIG. 3B), by afull-resolution comparison frame F2 (e.g., FIGS. 2C and 2D). Forexample, when the navigation device 100 has a fast movement, thesubpixel motion is not calculated; whereas, when the navigation device100 has a slow movement, the subpixel motion is calculated to improvethe tracking accuracy.

In addition, in the fast moving scenario, a moving distance of thenavigation device 100 can take a large ratio of the size of thereference frame F1 and the comparison frame F2, as shown in FIG. 6 forexample, to cause an overlap area between the reference frame F1 and thecomparison frame F2 to be smaller. In this case, if a part of pixel datais ignored in calculating displacement as described in the presentdisclosure, correct displacement may not be obtainable. Accordingly, inone non-limiting embodiment, the memory 17 further stores a displacementthreshold which is previously determined according to a size of a pixelarray of the image sensor 13. When the displacement calculated by theprocessor 15 according to a reference frame F1 and a partial-resolutioncomparison frame F2 is larger than the displacement threshold, theprocessor 15 does not ignore any pixel data of a next comparison frame(i.e. an image frame captured by the image sensor 13 after thecomparison frame F2) in calculating a next correlation search window.When the displacement calculated by the processor 15 is smaller than thedisplacement threshold, a power save mode is entered to calculate thecorrelation search window by the partial-resolution comparison windowF2.

FIG. 8 is a schematic diagram of the calculation results of a steady,one pixel upward motion and two pixels upward motion using 5×5correlation search windows respectively calculated by a full-resolutioncomparison window of the first embodiment (case 1), as well as by apartial-resolution comparison window of the third embodiment (case 2)and the fourth embodiment (case 3) of the present disclosure. It isclear that the calculation result calculated by the partial-resolutioncomparison window is not substantially influenced.

It should be mentioned that although the above embodiments are describedby ignoring a part of pixel data of the comparison frame as an example,the present disclosure is not limited thereto. In other embodiments, theprocessor ignores a part of pixel data of the reference frame to reducethe computation load thereof instead of ignoring the pixel data of thecomparison frame. The multiplication or subtraction operation betweenignored pixels in the reference frame and corresponding pixels in thecomparison frame is not calculated by the processor.

As mentioned above, under high speed sampling, the power consumption inperforming the position tracking is increased correspondingly.Accordingly, the present disclosure further provides a navigation device(e.g., FIG. 1) and a calculation method of a correlation search window(e.g. FIG. 7) that ignore a part of pixel data during calculating acorrelation search window to reduce the computation load (e.g.,multiplication or subtraction) of the processor. Not only the powerconsumption in calculation is reduced, the tracking accuracy will not bedegraded. In addition, the subpixel accuracy is obtainable bycalculating the correlation values for a second time using afull-resolution image frame.

Although the disclosure has been explained in relation to its preferredembodiment, it is not used to limit the disclosure. It is to beunderstood that many other possible modifications and variations can bemade by those skilled in the art without departing from the spirit andscope of the disclosure as hereinafter claimed.

What is claimed is:
 1. A navigation device, comprising: an image sensorconfigured to output a reference frame and a comparison frame, whereinthe reference frame is an image frame prior to the comparison frame; anda processor configured to calculate a correlation search window bychanging a relative position of the comparison frame with respect to thereference frame, wherein the processor ignores a part of pixel data ofthe reference frame in calculating each correlation value of thecorrelation search window, calculate a correlation peak of thecorrelation search window, calculate full-resolution correlation valuesof the correlation peak and adjacent correlation values thereof,respectively, according to the comparison frame and the reference framewithout ignoring pixel data, and mirror project the full-resolutioncorrelation values of the adjacent correlation values within thecorrelation search window as a part of adjacent correlation values,which are outside the correlation search window, of the correlation peakwhen the correlation peak is at an edge position of the correlationsearch window.
 2. The navigation device as claimed in claim 1, whereinthe ignored pixel data and the rest pixel data in the reference frameare distributed as a chessboard pattern.
 3. The navigation device asclaimed in claim 1, wherein the correlation search window is a 3×3correlation value array comprising 9 correlation values corresponding to9 relative positions of the comparison frame with respect to thereference frame, or a 5×5 correlation value array comprising 25correlation values corresponding to 25 relative positions of thecomparison frame with respect to the reference frame.
 4. The navigationdevice as claimed in claim 3, wherein the each correlation value of thecorrelation search window is a sum of multiplication or a sum ofsubtraction between corresponding pixels of the comparison frame and thereference frame at an associated relative position.
 5. The navigationdevice as claimed in claim 1, wherein the processor is furtherconfigured to calculate a displacement according to the correlationpeak.
 6. The navigation device as claimed in claim 5, further comprisinga memory configured to store a displacement threshold, wherein when thedisplacement is larger than the displacement threshold, the processor isconfigured not to ignore any pixel data of the reference frame whilecalculating a next correlation search window.
 7. The navigation deviceas claimed in claim 1, wherein the processor is further configured tocalculate a subpixel motion according to the correlation peak and theadjacent correlation values thereof in the correlation search window. 8.A navigation device, comprising: an image sensor configured to output areference frame and a comparison frame, wherein the comparison frame isan image frame prior to the comparison frame; and a processor configuredto calculate a correlation search window by changing a relative positionof the comparison frame with respect to the reference frame, not ignoreany pixel data of the comparison frame while calculating innercorrelation values of the correlation search window, and ignore a partof pixel data of the comparison frame while calculating edge correlationvalues surrounding the inner correlation values of the correlationsearch window.
 9. The navigation device as claimed in claim 8, whereinthe ignored pixel data and the rest pixel data in the comparison frameare distributed as a chessboard pattern.
 10. The navigation device asclaimed in claim 8, wherein the correlation search window is a 5×5correlation value array, the inner correlation values include 9correlation values of the correlation search window, and the edgecorrelation values include 16 correlation values of the correlationsearch window.
 11. The navigation device as claimed in claim 10, whereinthe 9 inner correlation values of the correlation search window iscalculated according to 9 relative positions of the comparison framewith respect to the reference frame, and the 16 edge correlation valuesof the correlation search window is calculated according to 16 relativepositions of the comparison frame with respect to the reference frame.12. The navigation device as claimed in claim 11, wherein eachcorrelation value of the correlation search window is a sum ofmultiplication or a sum of subtraction between corresponding pixels ofthe comparison frame and the reference frame at an associated relativeposition.
 13. The navigation device as claimed in claim 8, wherein theprocessor is further configured to calculate a correlation peak of thecorrelation search window, and calculate a displacement according to thecorrelation peak.
 14. The navigation device as claimed in claim 13,wherein the processor is configured to calculate a subpixel motionaccording to the correlation peak and adjacent correlation valuesthereof in the correlation search window.
 15. The navigation device asclaimed in claim 14, wherein when the correlation peak is at a positionof the edge correlation values of the correlation search window, theprocessor is further configured to calculate full-resolution correlationvalues of the correlation peak and the adjacent correlation values,respectively, according to the comparison frame without ignoring pixeldata and the reference frame.
 16. The navigation device as claimed inclaim 15, wherein the processor is further configured to mirror projectthe full-resolution correlation values of the adjacent correlationvalues within the correlation search window as a part of adjacentcorrelation values, which are outside the correlation search window, ofthe correlation peak to accordingly calculate the subpixel motion. 17.The navigation device as claimed in claim 14, wherein when thecorrelation peak is at a position of the inner correlation values of thecorrelation search window but not at a center position, the processor isfurther configured to calculate full-resolution correlation values ofthe adjacent correlation values at positions of the edge correlationvalues according to the comparison frame without ignoring pixel data andthe reference frame to accordingly calculate the subpixel motion.
 18. Acalculation method of a correlation search window of a navigationdevice, the navigation device comprising an image sensor and aprocessor, the calculation method comprising: sequentially outputting,by the image sensor, a reference frame and a comparison frame;calculating, by the processor, a correlation search window by changing arelative position of the comparison frame with respect to the referenceframe; not ignoring any pixel data of the reference frame whilecalculating, by the processor, inner correlation values of thecorrelation search window; and ignoring a part of pixel data of thereference frame while calculating, by the processor, edge correlationvalues surrounding the inner correlation values of the correlationsearch window.
 19. The calculation method as claimed in claim 18,wherein the correlation search window is a 5×5 correlation value array,and the inner correlation values include 9 correlation values of thecorrelation search window, and the edge correlation values include 16correlation values of the correlation search window.
 20. The calculationmethod as claimed in claim 18, wherein the ignored pixel data and therest pixel data in the reference frame are distributed as a chessboardpattern.